scholarly journals Dynamic Changes in Microbiome Composition Following Mare’s Milk Intake for Prevention of Collateral Antibiotic Effect

2021 ◽  
Vol 11 ◽  
Author(s):  
Almagul Kushugulova ◽  
Ulrike Löber ◽  
Saniya Akpanova ◽  
Kairat Rysbekov ◽  
Samat Kozhakhmetov ◽  
...  
Keyword(s):  
Antibiotic Therapy ◽  
Antibiotic Treatment ◽  
Amplicon Sequencing ◽  
Recovery Phase ◽  
Taxonomic Composition ◽  
Biologically Active ◽  
Microbiome Composition ◽  
16S Rrna Amplicon Sequencing ◽  
Immune Parameters ◽  
Antibiotic Effect

IntroductionProbiotics and prebiotics are widely used for recovery of the human gut microbiome after antibiotic treatment. High antibiotic usage is especially common in children with developing microbiome. We hypothesized that dry Mare’s milk, which is rich in biologically active substances without containing live bacteria, could be used as a prebiotic in promoting microbial diversity following antibiotic treatment in children. The present pilot study aims to determine the impacts of dry Mare’s milk on the diversity of gut bacterial communities when administered during antibiotic treatment and throughout the subsequent recovery phase.MethodsSix children aged 4 to 5 years and diagnosed with bilateral bronchopneumonia were prescribed cephalosporin antibiotics. During the 60 days of the study, three children consumed dry Mare’s milk whereas the other three did not. Fecal samples were collected daily during antibiotic therapy and every 5 days after antibiotic therapy. Total DNA was isolated and taxonomic composition of gut microbiota was analyzed by 16S rRNA amplicon sequencing. To assess the immune status of the gut, stool samples were analyzed by bead-based multiplex assays.ResultsMare’s milk treatment seems to prevent the bloom of Mollicutes, while preventing the loss of Coriobacteriales. Immunological analysis of the stool reveals an effect of Mare’s milk on local immune parameters under the present conditions.

scholarly journals Reversion of Gut Microbiota during the Recovery Phase in Patients with Asymptomatic or Mild COVID-19: Longitudinal Study

2021 ◽  
Vol 9 (6) ◽  
pp. 1237
Author(s):  
Han-Na Kim ◽  
Eun-Jeong Joo ◽  
Chil-Woo Lee ◽  
Kwang-Sung Ahn ◽  
Hyung-Lae Kim ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Gastrointestinal Symptoms ◽  
Amplicon Sequencing ◽  
Recovery Phase ◽  
Fecal Samples ◽  
Intestinal Microbes ◽  
Gut Dysbiosis ◽  
16S Rrna Amplicon Sequencing ◽  
Microbiome Data ◽  
Negative Conversion

Patients with COVID-19 have been reported to experience gastrointestinal symptoms as well as respiratory symptoms, but the effects of COVID-19 on the gut microbiota are poorly understood. We explored gut microbiome profiles associated with the respiratory infection of SARS-CoV-2 during the recovery phase in patients with asymptomatic or mild COVID-19. A longitudinal analysis was performed using the same patients to determine whether the gut microbiota changed after recovery from COVID-19. We applied 16S rRNA amplicon sequencing to analyze two paired fecal samples from 12 patients with asymptomatic or mild COVID-19. Fecal samples were selected at two time points: during SARS-CoV-2 infection (infected state) and after negative conversion of the viral RNA (recovered state). We also compared the microbiome data with those from 36 healthy controls. Microbial evenness of the recovered state was significantly increased compared with the infected state. SARS-CoV-2 infection induced the depletion of Bacteroidetes, while an abundance was observed with a tendency to rapidly reverse in the recovered state. The Firmicutes/Bacteroidetes ratio in the infected state was markedly higher than that in the recovered state. Gut dysbiosis was observed after infection even in patients with asymptomatic or mild COVID-19, while the composition of the gut microbiota was recovered after negative conversion of SARS-CoV-2 RNA. Modifying intestinal microbes in response to COVID-19 might be a useful therapeutic alternative.

scholarly journals Investigation of tylosin in feed of feedlot cattle and effects on liver abscess prevalence, and fecal and soil microbiomes and resistomes1

2019 ◽  
Vol 97 (11) ◽  
pp. 4567-4578 ◽  
Author(s):  
Margaret D Weinroth ◽  
Jennifer N Martin ◽  
Enrique Doster ◽  
Ifigenia Geornaras ◽  
Jennifer K Parker ◽  
...  
Keyword(s):  
Liver Abscess ◽  
Soil Microbial Communities ◽  
Amplicon Sequencing ◽  
Feedlot Cattle ◽  
Microbiome Composition ◽  
Soil Microbial ◽  
16S Rrna Amplicon Sequencing ◽  
Liver Abscesses ◽  
Geographical Regions ◽  
Antimicrobial Resistance Genes

Abstract Liver abscesses in feedlot cattle are detrimental to animal performance and economic return. Tylosin, a macrolide antibiotic, is used to reduce prevalence of liver abscesses, though there is variable efficacy among different groups of cattle. There is an increased importance in better understanding the etiology and pathogenesis of this condition because of growing concern over antibiotic resistance and increased scrutiny regarding use of antibiotics in food animal production. The objective of this study was to compare the microbiomes and antimicrobial resistance genes (resistomes) of feces of feedlot cattle administered or not administered tylosin and in their pen soil in 3 geographical regions with differing liver abscess prevalences. Cattle (total of 2,256) from 3 geographical regions were selected for inclusion based on dietary supplementation with tylosin (yes/no). Feces and pen soil samples were collected before harvest, and liver abscesses were identified at harvest. Shotgun and 16S rRNA amplicon sequencing were used to evaluate the soil and feces. Microbiome and resistome composition of feces (as compared by UniFrac distances and Euclidian distances, respectively) did not differ (P > 0.05) among tylosin or no tylosin-administered cattle. However, feedlot location was associated with differences (P ≤ 0.05) of resistomes and microbiomes. Using LASSO, a statistical model identified both fecal and soil microbial communities as predictive of liver abscess prevalence in pens. This model explained 75% of the variation in liver abscess prevalence, though a larger sample size would be needed to increase robustness of the model. These data suggest that tylosin exposure does not have a large impact on cattle resistomes or microbiomes, but instead, location of cattle production may be a stronger driver of both the resistome and microbiome composition of feces.

scholarly journals Inference based PICRUSt accuracy varies across sample types and functional categories

2019 ◽  
Author(s):  
Shan Sun ◽  
Roshonda B. Jones ◽  
Anthony A. Fodor
Keyword(s):  
16S Rrna ◽  
Gene Prediction ◽  
Amplicon Sequencing ◽  
Taxonomic Composition ◽  
Inference Models ◽  
16S Rrna Amplicon Sequencing ◽  
Gene Profiles ◽  
Metagenome Sequencing ◽  
The Cost ◽  
Functional Profiles

AbstractBackgroundDespite recent decreases in the cost of sequencing, shotgun metagenome sequencing remains more expensive compared with 16S rRNA amplicon sequencing. Methods have been developed to predict the functional profiles of microbial communities based on their taxonomic composition, and PICRUSt is the most widely used of these techniques. In this study, we evaluated the performance of PICRUSt by comparing the significance of the differential abundance of functional gene profiles predicted with PICRUSt to those from shotgun metagenome sequencing across different environments.ResultsWe selected 7 datasets of human, non-human animal and environmental (soil) samples that have publicly available 16S rRNA and shotgun metagenome sequences. As we would expect based on previous literature, strong Spearman correlations were observed between gene compositions predicted with PICRUSt and measured with shotgun metagenome sequencing. However, these strong correlations were preserved even when the sample labels were shuffled. This suggests that simple correlation coefficient is a highly unreliable measure for the performance of algorithms like PICRUSt. As an alternative, we compared the performance of PICRUSt predicted genes to metagenome genes in inference models associated with metadata within each dataset. With this method, we found reasonable performance for human datasets, with PICRUSt performing better for inference on genes related to “house-keeping” functions. However, the performance of PICRUSt degraded sharply outside of human datasets when used for inference.ConclusionWe conclude that the utility of PICRUSt for inference with the default database is likely limited outside of human samples and that development of tools for gene prediction specific to different non-human and environmental samples is warranted.

scholarly journals Maternal effects on early-life gut microbiome maturation in a wild nonhuman primate

2021 ◽  
Author(s):  
Alice Baniel ◽  
Lauren Petrullo ◽  
Arianne Mercer ◽  
Laurie Reitsema ◽  
Sierra Sams ◽  
...  
Keyword(s):  
Maternal Effects ◽  
Gut Microbiome ◽  
Early Life ◽  
Amplicon Sequencing ◽  
Microbial Colonization ◽  
Fecal Samples ◽  
Microbiome Composition ◽  
16S Rrna Amplicon Sequencing ◽  
Gut Colonization ◽  
First Time

Early-life gut microbial colonization is an important process shaping host physiology, immunity and long-term health outcomes in humans and other animals. However, our understanding of this dynamic process remains poorly investigated in wild animals, where developmental mechanisms can be better understood within ecological and evolutionary relevant contexts. Using 16s rRNA amplicon sequencing on 525 fecal samples from a large cohort of infant and juvenile geladas (Theropithecus gelada), we characterized gut microbiome maturation during the first three years of life and assessed the role of maternal effects in shaping offspring microbiome assembly. Microbial diversity increased rapidly in the first months of life, followed by more gradual changes until weaning. As expected, changes in gut microbiome composition and function with increasing age reflected progressive dietary transitions: in early infancy when infants rely heavily on their mother's milk, microbes that facilitate milk glycans and lactose utilization dominated, while later in development as graminoids are progressively introduced into the diet, microbes that metabolize plant complex polysaccharides became dominant. Furthermore, the microbial community of nursing infants born to first-time (primiparous) mothers was more "milk-oriented" compared to similarly-aged infants born to experienced (multiparous) mothers. Comparisons of matched mother-offspring fecal samples to random dyads did not support vertical transmission as a conduit for these maternal effects, which instead could be explained by slower phenotypic development (and associated slower gut microbiome maturation) in infants born to first-time mothers. Together, our findings highlight the dynamic nature of gut colonization

scholarly journals Effect of mare’s milk prebiotic supplementation on the gut microbiome and the immune system following antibiotic therapy

2020 ◽  
Vol 21 (11) ◽  
Author(s):  
Madiyar Nurgaziyev ◽  
YERMEK AITENOV ◽  
ZHANAGUL KHASSENBEKOVA ◽  
SANIYA AKPANOVA ◽  
KAIRAT RYSBEKOV ◽  
...  
Keyword(s):  
Immune System ◽  
Antibiotic Therapy ◽  
Antibiotic Treatment ◽  
Gut Microbiome ◽  
Taxonomic Composition ◽  
Rrna Gene ◽  
Total Dna ◽  
And Function ◽  
V3 Region

Abstract. Nurgaziyev M, Atenov Y, Khassenbekova Z, Akpanova S, Rysbekov K, Kozhakhmetov S, Nurgozhina A, Sergazy S, Chulenbayeva L, Ospanova Z, Tuyakova A, Mukhambetganov N, Sattybayeva R, Urazova S, Galymgozhina N, Zhumadilova A, Gulyaev A, Kushugulova A. 2020. Effect of mare’s milk prebiotic supplementation on the gut microbiome and the immune system following antibiotic therapy. Biodiversitas 21: 5065-5071. Antibiotic treatment can severely affect the gut microbiome for short-term and long-term consequences. Probiotic and prebiotic supplements are widely prescribed to modulate the composition and function of the human gut microbiome. The current study aims to determine the impacts of mare’s milk prebiotics on the diversity of gut bacterial communities and the local immune system when administered during and after a course of antibiotic therapy. Six children aged 4 to 5 years diagnosed with bilateral bronchopneumonia were prescribed cephalosporin (cefuroxime) antibiotics. During the 60 days of the study, three children consumed mare’s milk prebiotics, while the other three did not. Fecal samples were collected daily during antibiotic therapy and every five days after the last day of antibiotic treatment. Total DNA was isolated, and the taxonomic composition of the gut microbiome was analyzed by sequencing the 16S rRNA gene (V1-V3 region). The MULTIPLEX MAP platform was used to evaluate the local immune status. The relative abundance of 11 genera was reduced and did not recover until the last day of the study. The abundance of Bacteroides was not significantly altered in either group. Christensenella, Rothia, Abiotrophia, Acinetobacter, Anaerotruncus, Holdemania, and Turicibacter numbers were significantly increased on day five and remained at the same level during the study period. Cephalosporin administration also reduced the levels of pro-inflammatory and anti-inflammatory cytokines/chemokines (MIP1α, TNFα, GMCSF, GCSF, sCD40L, FGF2, TGFα, IL1α, and IP10).

scholarly journals Inference based accuracy of metagenome prediction tools varies across sample types and functional categories

2020 ◽  
Author(s):  
Shan Sun ◽  
Roshonda B. Jones ◽  
Anthony A. Fodor
Keyword(s):  
16S Rrna ◽  
Gene Prediction ◽  
Amplicon Sequencing ◽  
Taxonomic Composition ◽  
Inference Models ◽  
Prediction Tools ◽  
16S Rrna Amplicon Sequencing ◽  
Metagenome Sequencing ◽  
The Cost ◽  
Functional Profiles

Abstract Background: Despite recent decreases in the cost of sequencing, shotgun metagenome sequencing remains more expensive compared with 16S rRNA amplicon sequencing. Methods have been developed to predict the functional profiles of microbial communities based on their taxonomic composition. In this study, we evaluated the performance of three commonly used metagenome prediction tools (PICRUSt, PICRUSt2 and Tax4Fun) by comparing the significance of the differential abundance of predicted functional gene profiles to those from shotgun metagenome sequencing across different environments. Results: We selected 7 datasets of human, non-human animal and environmental (soil) samples that have publicly available 16S rRNA and shotgun metagenome sequences. As we would expect based on previous literature, strong Spearman correlations were observed between predicted gene compositions and gene relative abundance measured with shotgun metagenome sequencing. However, these strong correlations were preserved even when the abundance of genes were permuted across samples. This suggests that simple correlation coefficient is a highly unreliable measure for the performance of metagenome prediction tools. As an alternative, we compared the performance of genes predicted with PICRUSt, PICRUSt2 and Tax4Fun to sequenced metagenome genes in inference models associated with metadata within each dataset. With this approach, we found reasonable performance for human datasets, with the metagenome prediction tools performing better for inference on genes related to “house-keeping” functions. However, their performance degraded sharply outside of human datasets when used for inference. Conclusion: We conclude that the utility of PICRUSt, PICRUSt2 and Tax4Fun for inference with the default database is likely limited outside of human samples and that development of tools for gene prediction specific to different non-human and environmental samples is warranted.

scholarly journals On the robustness of inference of association with the gut microbiota in stool, swab and mucosal tissue samples

2021 ◽  
Author(s):  
Shan Sun ◽  
Xiangzhu Zhu ◽  
Xiang Huang ◽  
Harvey J. Murff ◽  
Reid M. Ness ◽  
...  
Keyword(s):  
Microbial Community ◽  
Gut Microbiota ◽  
Community Composition ◽  
Microbial Community Composition ◽  
Amplicon Sequencing ◽  
Taxonomic Composition ◽  
Mucosal Tissue ◽  
Tissue Samples ◽  
16S Rrna Amplicon Sequencing ◽  
Functional Profiles

AbstractThe gut microbiota plays an important role in human health and disease. Stool, swab and mucosal tissue samples have been used in individual studies to survey the microbial community but the consequences of using these different sample types are not completely understood. We previously reported differences in microbial community composition with 16S rRNA amplicon sequencing between stool, swab and mucosal tissue samples. Here, we extended the previous study to a larger cohort and performed shotgun metagenome sequencing of 1,397 stool, swab and mucosal tissue samples from 240 participants. Consistent with previous results, taxonomic composition of stool and swab samples was distinct, but still more similar to each other than mucosal tissue samples, which had a substantially different community composition, characterized by a high relative abundance of the mucus metabolizers Bacteroides and Subdoligranulum, as well as bacteria with higher tolerance for oxidative stress such as Escherichia. As has been previously reported, functional profiles were more uniform across sample types than taxonomic profiles with differences between stool and swab samples smaller, but mucosal tissue samples remained distinct from the other two types. When the taxonomic and functional profiles of different sample types were used for inference in association with host phenotypes of age, sex, body mass index (BMI), antibiotics or non-steroidal anti-inflammatory drugs (NSAIDs) use, hypothesis testing using either stool or swab gave broadly similar results, but inference performed on mucosal tissue samples gave results that were generally less consistent with either stool or swab. Our study represents an important resource for the experimental design of studies aimed to understand microbiota perturbations specific to defined micro niches within the human intestinal tract.

scholarly journals Coffee Consumption Modulates Amoxicillin-Induced Dysbiosis in the Murine Gut Microbiome

2021 ◽  
Vol 12 ◽  
Author(s):  
Emma Diamond ◽  
Katharine Hewlett ◽  
Swathi Penumutchu ◽  
Alexei Belenky ◽  
Peter Belenky
Keyword(s):  
Gut Microbiome ◽  
Burkholderia Cepacia ◽  
Coffee Consumption ◽  
Amplicon Sequencing ◽  
Antibiotic Use ◽  
Fecal Microbiome ◽  
Microbiome Composition ◽  
16S Rrna Amplicon Sequencing ◽  
Caffeinated Coffee

The microbiome is essential for host health, and perturbations resulting from antibiotic use can lead to dysbiosis and disease. Diet can be a powerful modulator of microbiome composition and function, with the potential to mitigate the negative effects of antibiotic use. Thus, it is necessary to study the impacts of diet and drug interactions on the gut microbiome. Coffee is a commonly consumed beverage containing many compounds that have the potential to affect the microbiome, including caffeine, polyphenols, and fiber. We supplemented mice with caffeinated and decaffeinated coffee in conjunction with amoxicillin, and used 16S rRNA amplicon sequencing of fecal samples to investigate changes in diversity and composition of the murine fecal microbiome. We found that antibiotics, regardless of coffee supplementation, caused significant disruption to the murine fecal microbiome, enriching for Proteobacteria, Verrucomicrobia, and Bacteroidetes, but reducing Firmicutes. While we found that coffee alone did not have a significant impact on the composition of the fecal microbiome, coffee supplementation did significantly affect relative abundance metrics in mice treated with amoxicillin. After caffeinated coffee supplementation, mice treated with amoxicillin showed a smaller increase in Proteobacteria, specifically of the family Burkholderiaceae. Correspondingly we found that in vitro, Burkholderia cepacia was highly resistant to amoxicillin, and that it was inhibited by concentrations of caffeine and caffeinated coffee comparable to levels of caffeine in murine ceca. Overall, this work shows that coffee, and possibly the caffeine component, can impact both the microbiome and microbiome members during antibiotic exposure.

scholarly journals Life Inside a Dinosaur Bone: a Thriving Microbiome

2018 ◽  
Author(s):  
Evan T. Saitta ◽  
Renxing Liang ◽  
Chui Y. Lau ◽  
Caleb M. Brown ◽  
Nicholas R. Longrich ◽  
...  
Keyword(s):  
16S Rrna ◽  
Open System ◽  
Potential Role ◽  
Organic Molecules ◽  
Amplicon Sequencing ◽  
Biologically Active ◽  
Bone Collagen ◽  
Fossil Bone ◽  
16S Rrna Amplicon Sequencing ◽  
Fossil Bones

AbstractFossils were long thought to lack original organic material, but the discovery of organic molecules in fossils and sub-fossils, thousands to millions of years old, has demonstrated the potential of fossil organics to provide radical new insights into the fossil record. How long different organics can persist remains unclear, however. Non-avian dinosaur bone has been hypothesised to preserve endogenous organics including collagen, osteocytes, and blood vessels, but proteins and labile lipids are unstable during diagenesis or over long periods of time. Furthermore, bone is porous and an open system, allowing microbial and organic flux. Some of these organics within fossil bone have therefore been identified as either contamination or microbial biofilm, rather than original organics. Here, we use biological and chemical analyses of Late Cretaceous dinosaur bones and sediment matrix to show that dinosaur bone hosts a diverse microbiome. Fossils and matrix were freshly-excavated, aseptically-acquired, and then analysed using microscopy, spectroscopy, chromatography, spectrometry, DNA extraction, and 16S rRNA amplicon sequencing. The fossil organics differ from modern bone collagen chemically and structurally. A key finding is that 16S rRNA amplicon sequencing reveals that the subterranean fossil bones host a unique, living microbiome distinct from that of the surrounding sediment. Even in the subsurface, dinosaur bone is biologically active and behaves as an open system, attracting microbes that might alter original organics or complicate the identification of original organics. These results suggest caution regarding claims of dinosaur bone ‘soft tissue’ preservation and illustrate a potential role for microbial communities in post-burial taphonomy.

scholarly journals Multiomic Approach to Analyze Infant Gut Microbiota: Experimental and Analytical Method Optimization

Biomolecules ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 999
Author(s):  
Helena Torrell ◽  
Adrià Cereto-Massagué ◽  
Polina Kazakova ◽  
Lorena García ◽  
Héctor Palacios ◽  
...  
Keyword(s):  
16S Rrna ◽  
Gut Microbiota ◽  
Variable Region ◽  
Amplicon Sequencing ◽  
Taxonomic Composition ◽  
Intestinal Microbiome ◽  
Fecal Samples ◽  
16S Rrna Amplicon Sequencing ◽  
Method Optimization ◽  
Feature Selection Approach

Background: The human intestinal microbiome plays a central role in overall health status, especially in early life stages. 16S rRNA amplicon sequencing is used to profile its taxonomic composition; however, multiomic approaches have been proposed as the most accurate methods for study of the complexity of the gut microbiota. In this study, we propose an optimized method for bacterial diversity analysis that we validated and complemented with metabolomics by analyzing fecal samples. Methods: Forty-eight different analytical combinations regarding (1) 16S rRNA variable region sequencing, (2) a feature selection approach, and (3) taxonomy assignment methods were tested. A total of 18 infant fecal samples grouped depending on the type of feeding were analyzed by the proposed 16S rRNA workflow and by metabolomic analysis. Results: The results showed that the sole use of V4 region sequencing with ASV identification and VSEARCH for taxonomy assignment produced the most accurate results. The application of this workflow showed clear differences between fecal samples according to the type of feeding, which correlated with changes in the fecal metabolic profile. Conclusion: A multiomic approach using real fecal samples from 18 infants with different types of feeding demonstrated the effectiveness of the proposed 16S rRNA-amplicon sequencing workflow.

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